code: def create_debug_info_from_selected_models(
      output: Dict[str, object],
      selected_models: List[dict],
      new_style_rule: bool,
  ):
      model_dict = {
          "asset_info": {},  # maps asset name -> dict of asset metadata like hashes
          "is_new_style_rule": new_style_rule,
      }
  
      for model in selected_models:
          model_info = model["model"]
          asset = model_info["asset"]
          hash = model_info["md5_hash"]
  
          asset_info = model_dict["asset_info"].setdefault(asset, {})
  
          asset_info.setdefault("md5_hash", []).append(hash)
  
      # Will later be used in gen_oplist to generate the model/version/asset checking
      output["debug_info"] = [json.dumps(model_dict)]
  
file_path: pytorch/tools/code_analyzer/gen_operators_yaml.py
imports: import argparse
  import json
  import sys
  from typing import Any, Dict, List, Optional
  import yaml
  from gen_op_registration_allowlist import canonical_name, gen_transitive_closure, load_op_dep_graph
  from torchgen.selective_build.operator import merge_operator_dicts, SelectiveBuildOperator
  from torchgen.selective_build.selector import merge_kernel_metadata
label_desc: Use image node_id 5 for calling a global function with example usage: create_debug_info_from_selected_models(output, selected_models, new_style_rule) without return types